Hands-on activities associated with the Ecological Forecasting book and graduate class
Switch branches/tags
Nothing to show
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
data
images
tutorials
.gitignore
.travis.yml
Chapter_06_FittingUncertainties.Rmd
Chapter_06_HierBayes.Rmd
Chapter_11_UncertAnalysis.Rmd
DESCRIPTION
Exercise_01_RPrimer.Rmd
Exercise_02_Logistic.Rmd
Exercise_03_BigData.Rmd
Exercise_04_PairCoding.Rmd
Exercise_05B_Regression.Rmd
Exercise_05_JAGS.Rmd
Exercise_06_StateSpace.Rmd
Exercise_07_TreeRings.Rmd
Exercise_09_KalmanFilter.Rmd
Exercise_10_ParticleFilter.Rmd
Exercise_11_ModelAssessment.Rmd
Exercise_12_DecisionSupport.Rmd
LICENSE
README.md

README.md

EF_Activities

Hands-on activities associated with the Ecological Forecasting book and graduate class

Book: Dietze, M. 2017. Ecological Forecasting. Princeton University Press https://ecoforecast.org/book

List of activities by Chapter:

Chapter 1: Introduction

  • Exercise 01 - R primer

Chapter 2: From Models to Forecasts

  • Exercise 02 - From models to forecasts

Chapter 3: Data, Large and Small

  • Exercise 03 - Tools for working with data

Chapter 4: Scientific Workflows and the Informatics of Model-Data Fusion

  • Exercise 04 - Pair Coding and Github

Chapter 5: Introduction to Bayes

  • Exercise 05 - JAGS primer

  • Exercise 05B - Bayesian Regression

Chapter 6:Characterizing Uncertainty

  • Chapter 06 - Fitting Uncertainties

  • Chapter 06 - Hierarchical Bayes

Chapter 8: Latent Variables and State-Space Models

  • Exercise 06 - State Space models

Chapter 9: Fusing Data Sources

  • Exercise 07 - Fusing time-series data

Chapter 11: Propagating, Analyzing, and Reducing Uncertainty

  • Chapter 11 - Uncertainty Propagation and Analysis

Chapter 13: Data Assimilation 1: Analytical Methods

  • Exercise 09 - Kalman Filter

Chapter 14: Data Assimilation 2: Monte Carlo Methods

  • Exercise 10 - Particle Filter

Chapter 16: Assessing Model Performance

  • Exercise 11 - Model Assessment

Chapter 17: Projection and Decision Support

  • Exercise 12 - Decision Support

In addition this repository contains the following folders:

  • data - Data files used in the exercises
  • images - Image files embedded in the exercises
  • tutorial - Additional tutorials contributed by previous students

For a list of Git and Github tutorials see http://gist.github.com/Pakillo/63c15c700c9c76fe8032